This thesis introduces a design combining an emerging area in robotics with a well established mathematical research topic: swarm intelligence and Voronoi tessellations, respectively. The main objective for this research is to design an economical and robust swarm system to achieve distributed control. This research combines swarm intelligence with Voronoi tessellations to localize a source and create formations. Extensive software coding must be implemented for this design, such as the development of a discrete centroidal Voronoi tessellation (CVT) algorithm. The ultimate purpose of this research is to advance the existing Mobile Actuator and Sensor Network (MASnet) platform to eventually develop a cooperative robot team that can sense, predict, and nally neutralize a diusion process. Previous work on the MASnet platform has served as a foundation for this research. While growing closer to the MASnet goal, results also provide stimulating discoveries for mathematical and swarm research areas.

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Formation control is a classical problem and has been a prime topic of interest among the scientific community in the past few years. Although a vast amount of literature exists in this field, there are still many open questions that require an in-depth understanding and a new perspective. This thesis contributes towards exploring the wide dimensions of formation control and implementing a formation control scheme for a group of multi-agent systems. These systems are autonomous in nature and are represented by double integrated dynamics. It is assumed that the agents are connected in an undirected graph and use a leader-follower architecture to reach formation when the leading agent is given a velocity that is piecewise constant. A MATLAB code is written for the implementation of formation and the consensus-based control laws are verified. Understanding the effects on formation due to a fixed formation geometry is also observed and reported. Also, a link that describes the functional similarity between desired formation geometry and the Laplacian matrix has been observed. The use of Laplacian matrix in stability analysis of the formation is of special interest.

International Telemetering Conference Proceedings / November 04-07, 1991 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The Gulf Range Drone Control Upgrade System (GRDCUS) Mobile Control System (GMCS) is an integral part of the test ranges located on the Gulf of Mexico. This paper begins with a brief overview of the current Gulf Range systems. These systems consist of five major components: ground stations, ground computer systems, data link/transponders, consoles, and software. The GMCS van contains many of these components to provide a stand-alone range capability for remote operations. This paper describes the development and assembly of the GMCS van and focuses on the on-board computer systems, consoles, and data link technology. An overall system engineering approach was used during GMCS development and is highlighted through the use of rapid prototyping. This methodology and the lessons learned are presented in the paper. Suggestions for future applications are considered.

Traditionally robots are controlled using devices like joysticks, keyboards, mice and other similar human computer interface (HCI) devices. Although this approach is effective and practical for some cases, it is restrictive only to healthy individuals without disabilities, and it also requires the user to master the device before its usage. It becomes complicated and non-intuitive when multiple robots need to be controlled simultaneously with these traditional devices, as in the case of Human Swarm Interfaces (HSI). This work presents a novel concept of using human bio-signals to control swarms of robots. With this concept there are two major advantages: Firstly, it gives amputees and people with certain disabilities the ability to control robotic swarms, which has previously not been possible. Secondly, it also gives the user a more intuitive interface to control swarms of robots by using gestures, thoughts, and eye movement. We measure different bio-signals from the human body including Electroencephalography (EEG), Electromyography (EMG), Electrooculography (EOG), using off the shelf products. After minimal signal processing, we then decode the intended control action using machine learning techniques like Hidden Markov Models (HMM) and K-Nearest Neighbors (K-NN). We employ formation controllers based on distance and displacement to control the shape and motion of the robotic swarm. Comparison for ground truth for thoughts and gesture classifications are done, and the resulting pipelines are evaluated with both simulations and hardware experiments with swarms of ground robots and aerial vehicles.

<p>This thesis contains new results on the problem of coordinating a group of vehicles. The main motivation driving this work is the development of control laws that steer individual members of a formation, such that desired group behavior emerges. Special attention is paid to analysis of coordination issues, in particular formation control of marine craft where robustness to unknown environmental forces is important. Coordinated control applications for marine craft include: underway replenishment, maintaining a formation for increased safety during travel and instrument resolution, and cooperative transportation. A review of formation control structures is given, together with a discussion of special issues that arise in coordination of independent vehicles.</p><p>The main contributions of this thesis may be grouped into two categories:</p><p>• Path-following designs for controlling a group of vehicles</p><p>• Multi-body motivated formation modeling and control</p><p>A previously developed path following design is used to control a group of vehicles by synchronizing the individual path parameters. The path following design is advantageous since the path parameter, i.e., that parameter which determines position along a path, is scalar; hence coordination is achieved with a little amount of real-time communication. The path following design is also extended to the output-feedback case for systems where only parts of the state vector are known. The path following scheme is exploited further in a passivity-based design for coordination where the structural properties render an extended selection of functions for synchronization available. Performance and robustness properties in different operational conditions can be enhanced with a careful selection of these functions. Two designs are presented; a cascaded interconnection where a consensus system provides synchronized path parameters as input to the individual path following systems renders time-varying formations possible and increases robustness to communication problems; a feedback interconnection which is more robust to vehicle failures. Both designs are extended to sampled-data designs where plant and controller dynamics are updated in continuous-time and path parameters are exchanged over a communication network where transmission occurs at discrete intervals. Bias estimation is included to provide integral action against slowlyvarying environmental forces and model uncertainties.</p><p>A scheme for formation modeling and control, inspired by analytical mechanics of multi-body systems and Lagrangian multipliers, is proposed. In this approach to formation control, various formation behaviors are determined by imposing constraint functions on group members. Several examples illustrate these formation behaviors. The stabilization scheme presented is made more robust with respect to unknown time-varying disturbances. In addition, the scheme is extended towards adaptive estimation of unknown plant and parameters. Furthermore, it can be applied with no major modifications to the case of position control for a single vehicle.</p><p>The formation control scheme is such that it may be used in combination with a set of position control laws for a single vessel, thus enabling the designer to choose from a large class of control laws available in the literature. The input-to-state stability (ISS) framework is utilised to investigate robustness to environmental and communication disturbances. A loop-transform, together with the ISS framework, yields an upper bound on the inter-vessel time delay below which formation stability is maintained.</p>

This thesis contains new results on the problem of coordinating a group of vehicles. The main motivation driving this work is the development of control laws that steer individual members of a formation, such that desired group behavior emerges. Special attention is paid to analysis of coordination issues, in particular formation control of marine craft where robustness to unknown environmental forces is important. Coordinated control applications for marine craft include: underway replenishment, maintaining a formation for increased safety during travel and instrument resolution, and cooperative transportation. A review of formation control structures is given, together with a discussion of special issues that arise in coordination of independent vehicles. The main contributions of this thesis may be grouped into two categories: • Path-following designs for controlling a group of vehicles • Multi-body motivated formation modeling and control A previously developed path following design is used to control a group of vehicles by synchronizing the individual path parameters. The path following design is advantageous since the path parameter, i.e., that parameter which determines position along a path, is scalar; hence coordination is achieved with a little amount of real-time communication. The path following design is also extended to the output-feedback case for systems where only parts of the state vector are known. The path following scheme is exploited further in a passivity-based design for coordination where the structural properties render an extended selection of functions for synchronization available. Performance and robustness properties in different operational conditions can be enhanced with a careful selection of these functions. Two designs are presented; a cascaded interconnection where a consensus system provides synchronized path parameters as input to the individual path following systems renders time-varying formations possible and increases robustness to communication problems; a feedback interconnection which is more robust to vehicle failures. Both designs are extended to sampled-data designs where plant and controller dynamics are updated in continuous-time and path parameters are exchanged over a communication network where transmission occurs at discrete intervals. Bias estimation is included to provide integral action against slowlyvarying environmental forces and model uncertainties. A scheme for formation modeling and control, inspired by analytical mechanics of multi-body systems and Lagrangian multipliers, is proposed. In this approach to formation control, various formation behaviors are determined by imposing constraint functions on group members. Several examples illustrate these formation behaviors. The stabilization scheme presented is made more robust with respect to unknown time-varying disturbances. In addition, the scheme is extended towards adaptive estimation of unknown plant and parameters. Furthermore, it can be applied with no major modifications to the case of position control for a single vehicle. The formation control scheme is such that it may be used in combination with a set of position control laws for a single vessel, thus enabling the designer to choose from a large class of control laws available in the literature. The input-to-state stability (ISS) framework is utilised to investigate robustness to environmental and communication disturbances. A loop-transform, together with the ISS framework, yields an upper bound on the inter-vessel time delay below which formation stability is maintained.

In this thesis, we consider problems connected to navigation and tracking for autonomousrobots under the assumption of constraints on sensors and kinematics. We study formation controlas well as techniques for filtering and smoothing of noise contaminated input. The scientific contributions of the thesis comprise five papers.In Paper A, we propose three cascaded, stabilizing formation controls for multi-agent systems.We consider platforms with non-holonomic kinematic constraints and directional rangesensors. The resulting formation is a leader-follower system, where each follower agent tracksits leader agent at a specified angle and distance. No inter-agent communication is required toexecute the controls. A switching Kalman filter is introduced for active sensing, and robustnessis demonstrated in experiments and simulations with Khepera II robots.In Paper B, an optimization-based adaptive Kalman filteringmethod is proposed. The methodproduces an estimate of the process noise covariance matrix Q by solving an optimization problemover a short window of data. The algorithm recovers the observations h(x) from a system˙ x = f (x), y = h(x)+v without a priori knowledge of system dynamics. The algorithm is evaluatedin simulations and a tracking example is included, for a target with coupled and nonlinearkinematics. In Paper C, we consider the problem of estimating a closed curve in R2 based on noisecontaminated samples. A recursive control theoretic smoothing spline approach is proposed, thatyields an initial estimate of the curve and subsequently computes refinements of the estimateiteratively. Periodic splines are generated by minimizing a cost function subject to constraintsimposed by a linear control system. The optimal control problem is shown to be proper, andsufficient optimality conditions are derived for a special case of the problem using Hamilton-Jacobi-Bellman theory.Paper D continues the study of recursive control theoretic smoothing splines. A discretizationof the problem is derived, yielding an unconstrained quadratic programming problem. Aproof of convexity for the discretized problem is provided, and the recursive algorithm is evaluatedin simulations and experiments using a SICK laser scanner mounted on a PowerBot from ActivMedia Robotics. Finally, in Paper E we explore the issue of optimal smoothing for control theoretic smoothingsplines. The output of the control theoretic smoothing spline problem is essentially a tradeoff between faithfulness to measurement data and smoothness. This tradeoff is regulated by the socalled smoothing parameter. In Paper E, a method is developed for estimating the optimal valueof this smoothing parameter. The procedure is based on general cross validation and requires noa priori information about the underlying curve or level of noise in the measurements. / QC 20100722

Considered in this research is a framework for effective formation control of multirobot systems in dynamic environments. The basic formation control involves two important considerations: (1) Real-time trajectory generation algorithms for distributed control based on nominal agent models, and (2) robust tracking of reference trajectories under model uncertainties. Proposed is a two-layer hierarchical architecture for collectivemotion control ofmultirobot nonholonomic systems. It endows robotic systems with the ability to simultaneously deal with multiple tasks and achieve typical complex formation missions, such as collisionfree maneuvers in dynamic environments, tracking certain desired trajectories, forming suitable patterns or geometrical shapes, and/or varying the pattern when necessary. The study also addresses real-time formation tracking of reference trajectories under the presence of model uncertainties and proposes robust control laws such that over each time interval any tracking errors due to system uncertainties are driven down to zero prior to the commencement of the subsequent computation segment. By considering a class of nonlinear systems with favorable finite-time convergence characteristics, sufficient conditions for exponential finite-time stability are established and then applied to distributed formation tracking controls. This manifests in the settling time of the controlled system being finite and no longer than the predefined reference trajectory segment computing time interval, thus making tracking errors go to zero by the end of the time horizon over which a segment of the reference trajectory is generated. This way the next segment of the reference trajectory is properly initialized to go into the trajectory computation algorithm. Consequently this could lead to a guarantee of desired multi-robot motion evolution in spite of system uncertainties. To facilitate practical implementation, communication among multi-agent systems is considered to enable the construction of distributed formation control. Instead of requiring global communication among all robots, a distributed communication algorithm is employed to eliminate redundant data propagation, thus reducing energy consumption and improving network efficiency while maintaining connectivity to ensure the convergence of formation control.

Navigation of a group of autonomous agents that are needed to maintain a formation is a challenging task which has not been studied much in especially 3-D terrains. This thesis presents a novel approach to collision free path finding of multiple agents preserving a predefined formation in a 3-D terrain. The proposed method could be used in many areas like navigation of semi-automated forces (SAF) at unit level in military simulations and non player characters (NPC) in computer games. The proposed path finding algorithm first computes an optimal path from an initial point to a target point after analyzing the 3-D terrain data from which it constructs a weighted graph. Then, it employs a real-time path finding algorithm specifically designed to realize the navigation of the group from one way point to the successive one on the optimal path generated at the previous stage, preserving the formation and avoiding collision both. A software was developed to test the methods discussed here.